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t’s a cliché to say that the world is more uncertain than ever before, but few realize just how much uncertainty has increased over the past 50 years. To illustrate this, consider that patent applications in the U.S. have increased by 6x (from 100k to 600k annually) and, worldwide, start-ups have increased from 10 million to almost 100 million per year. That means new technologies and new competitors are hitting the market at an unprecedented rate. Although uncertainty is accelerating, it isn’t affecting all industries the same way. That’s because there are two primary types of uncertainty — demand uncertainty (will customers buy your product?) and technological uncertainty (can we make a desirable solution?) — and how much uncertainty your industry faces depends on the interaction of the two. Demand uncertainty arises from the unknowns associated with solving any problem, such as hidden customer preferences. The more unknowns there are about customer preferences, the greater the demand uncertainty. For example, when Rent the Runway founder Jenn Hyman came up with the idea to rent designer dresses over the internet, demand uncertainty was high because no one else was offering this type of service. In contrast, when Samsung and Sony were deciding whether to launch LED TVs, which offered better picture quality than plasma TVs at a slightly higher price, there was lower uncertainty about demand because customers were already buying TVs. Technological uncertainty results from unknowns regarding the technologies that might emerge or be combined to create a new solution. For example, a wide variety of clean technologies (including wind, solar, and hydrogen) are vying to power vehicles and cities at the same time that a wide variety of medical technologies (chemical, biotechnological, genomic, and robotic) are being developed to treat diseases. As the overall rate of invention across industries increases, so does technological uncertainty. Consider the 2×2 matrix below. The horizontal axis plots each industry based on technological uncertainty, measured as the average R&D expenditures as a percentage of sales in the industry over the past ten years. The vertical axis plots each industry’s demand uncertainty, measured as an equal weighting of industry revenue volatility, or change, over the past 10 years and percentage of firms in the industry that entered or exited during that same time period. Although these are imperfect measures, they identify the industries facing the highest, and lowest baseline levels of uncertainty. https://hbrblogs.files.wordpress.com/2014/09/demandandtech.gif The table below ranks industries into the top 10 and bottom 10. https://hbrblogs.files.wordpress.com/2014/09/industriesrankedblue.gif Where does your industry sit? If your industry is in the lower left quadrant, or in the bottom 10 in the above table, you face relatively low baseline uncertainty for both demand and technology. Examples of industries here include providers of personal services, such as hair styling and dry cleaning, who have used similar technologies to provide solutions for well-known demands. By contrast, if you’re in the lower-right quadrant, you can generally predict demand but the challenge you face is technological uncertainty. For example, insurance companies face technological uncertainty that comes from how big data and analytics investments will drive revenue; whereas demand is based on highly predictable demographics. If you’re in the upper-left quadrant, you are with industries that face high demand uncertainty but low technological uncertainty. For example, restaurants and hotels often have difficulty predicting demand for their services, because many factors influence whether, when, and where people eat out or travel. However, the technologies used to offer food or lodging have not changed dramatically over the years. Finally, industries in the upper-right quadrant — such as software, pharmaceuticals, and medical equipment — face high uncertainty in both demand and technology. For example, who would have predicted that medical robots would perform surgeries? When Intuitive Surgical launched the Da Vinci System medical robot — which allows surgeons to operate using 3-D visualization and four robotic arms — the company faced significant technical as well as demand uncertainty. If you’re in the upper right quadrant — or in the top 10 most uncertain industries as shown in the Table — you require greater innovation management skills than industries in the other quadrants or in the bottom 10. In fact, among the top 10 companies of the Forbes Most Innovative Companies list(since 2011 when we started the list), more than 80% of the most innovative companies compete in industries in the top right quadrant. In other words, if you are in a high uncertainty industry, you must excel at innovation…or die. A new set of tools and perspectives — such as, for example, design thinking, lean start-up, agile development — are emerging in many disparate fields and revolutionizing the way managers in established companies successfully create, refine, and bring new ideas to market in conditions of high uncertainty. In our new book, The Innovator’s Method, we show how managers can adapt these tools, in an end-to-end process, for managing innovation. For example, companies that excel at resolving demand uncertainty become experts at design thinking and validating concepts through rapid experimentation with customers. Successful software companies like Google, Intuit, and Salesforce.com churn out their “beta” or “labs” products that effectively test demand for new products. When Google software engineer Paul Bucheit had ideas for Gmail and AdSense (the system that placed advertisements based on keywords in your Gmail messages, search, or website) he found he was often fighting against the opinions of leaders. But fortunately, experiments with customers trump opinions at Google. Following the advice of then CEO Eric Schmidt to “get 100 happy users inside Google,” Bucheit prototyped solutions that eventually proved demand and won the day. Today, AdSense generates $10 billion in annual revenue for Google. Companies that excel at resolving technological uncertainty often develop a broader technology palette. For example, to help start-up teams generate a broad list of solutions, Intuit identified and hired experts in technologies related to mobile devices, social media, user interaction, collaboration, data, and the like. These experts are valuable for broadening solution searches, and they help teams identify what is technologically feasible. At biotech Regeneron, the company pioneered a new experimentation platform — “humanized” mice that allowed them to test drug effects more rapidly and reliably — that dramatically increased their ability to test various technology solutions to problems. The bottom line is that success requires an understanding of how much uncertainty you face and the ability to manage those uncertainties in new ways. How much uncertainty does your industry face? Ask yourself the following questions: *Have new technologies or startups started to threaten my company or my industry? *Over the past five years have new competitors entered the market and captured 10% share by targeting our customers with a different value proposition than what we offer? *Over the past five years have we begun to see customer preferences change, resulting in a different mix of products and services being demanded? *Have you recently started offering (or are planning to offer) a product or service that has never been offered before? If you answered “yes” to the first two questions, you’re likely sitting in a business with high technological uncertainty; if “yes” to the last two questions, you’re probably dealing with high demand uncertainty.